Skill UI

This skill facilitates structured, bidirectional reading and knowledge synthesis for academic texts, theories, and articles. It forces users to first capture the source material's original intent, before critically mapping its relationships, conflicts, and absorptions against the CrossFrame framework. It ensures structured output with clear source boundaries, making it ideal for deep learning and scholarly work.

This skill extracts full transcripts and rich metadata from a single YouTube video URL. It uses yt-dlp to download subtitles, cleans VTT timing markers, and pulls video details (title, channel, date). The output is a structured, queryable Markdown file, ideal for populating a personal knowledge vault and enabling downstream knowledge graph extraction or content repurposing.

This skill addresses vague or ambiguous user requests by initiating a structured, multi-round questioning process. Instead of making assumptions, it systematically clarifies dimensions like audience, scope, tone, and format across several rounds (up to three). This structured approach ensures the resulting output is highly accurate and requires minimal revision cycles.